Across Sylvester, artificial intelligence advanced cancer care as a powerful partner for researchers and clinicians, enabling earlier detection, more personalized treatment, deeper insight into disease and more.
Seeing Cancer Sooner
Sylvester is co-leading the PRISM Trial (Pragmatic Randomized Trial of Artificial Intelligence for Screening Mammography) to evaluate whether AI can help radiologists interpret mammograms more accurately. The study randomly assigns hundreds of thousands of mammograms to be read either by a radiologist alone or with FDA-cleared AI assistance. Jose Net, M.D., director of breast imaging services at Sylvester, is co-principal investigator of the first major randomized trial using AI to improve breast cancer screening in the U.S.
Insight That Guides Care
Researchers from Sylvester and the Desai Sethi Urology Institute (DSUI) used AI to analyze urine biomarkers in prostate cancer patients and predict cancer aggressiveness with 95% accuracy, outperforming other validated tools. Principal investigator Sanoj Punnen, M.D., co-chair of Sylvester’s Genitourinary Site Disease Group, and co-leader of the Cancer Control Program and assistant director of clinical research, is working to bring this test quickly into clinics to guide care. Similarly, C. Ola Landgren, M.D., Ph.D., director of Sylvester Myeloma Institute and co-leader of Translational and Clinical Oncology, received the HealthTree Foundation’s 2025 Innovation Award for CORAL, a research innovation that uses AI to predict individual patient outcomes and guide treatment decisions.
Unlocking New Understanding
AI also opened new frontiers in understanding cancer at its most fundamental level. Sylvester researcher Martin Rivas, Ph.D., used AI-driven analytics to uncover subtle genome patterns that may predispose individuals to lymphoma, potentially guiding future treatments.
Sylvester researchers led an international effort to add data from individuals with African ancestry to AI-powered studies of prostate, breast and gynecological cancers. “AI is allowing us to discover things we wouldn’t necessarily find on our own,” said principal investigator Sophia George, Ph.D.
Through the Catalysts for Cure initiative, launched in 2024 to support innovative, collaborative projects between Sylvester and UM’s College of Arts and Sciences, researchers combined AI and biophysics to engineer a vaccine and delivery system against the virus that causes adult T cell leukemia/lymphoma.
A new AI model predicts where DNA carries methylation marks, chemical tags that can silence genes and play a role in cancer. Built with technology similar to generative AI tools like DALL-E, the model could accelerate research on cancer and other conditions. The study was co-led by Maria “Ken” Figueroa, M.D., associate director for translational research, and Yan Guo, Ph.D., director of the biostatistics and bioinformatics shared resource.
Listening More Closely
AI was integrated into My Wellness Check, an electronic questionnaire that tracks patient well-being and alerts care teams when support is needed. “By integrating clinical and patient-reported data with AI-powered risk assessment and tailored interventions, we’re able to deliver smarter, evidence-based care,” said Frank Penedo, Ph.D., associate director for population sciences and director of the Sylvester Cancer Survivorship and Supportive Care Institute.
AI also helped researchers pinpoint which patients are most at risk for side effects from immune checkpoint inhibitors. A team led by Patricia Moreno, Ph.D., lead of Evidence-Based Survivorship Supportive Care, is using machine learning to predict who is most likely to experience troublesome side effects.
“As with all uses of technology,” Dr. Moreno said, “it’s really about supporting patients and helping them live as well as possible while they receive cancer treatment.”